CVE-2026-25087: Apache Arrow Potential Use-after-free When Reading IPC Vulnerability

HIGH
Advisory Identifier: GHSA-rgxp-2hwp-jwgg
Share
CVSS 7.0
CWE-416
Published
Advisory Summary

CVE-2026-25087 is a HIGH (CVSS 7.0) potential use-after-free when reading ipc vulnerability (CWE-416: Use After Free) affecting Apache Arrow libraries in the PyPI ecosystem. The issue involves potential use-after-free when reading ipc file with pre-buffering. Remediation is available by upgrading affected packages to version 23.0.1.

CVE-2026-25087 at a Glance

CVE Identifier CVE-2026-25087
GHSA Identifier GHSA-rgxp-2hwp-jwgg
Severity HIGH
CVSS v3.1 Base Score 7.0
CWE Classification CWE-416: Use After Free
Affected Product Apache Arrow
Package Ecosystem PyPI
Published Date
Last Updated

Security Impact

CVSS: 7.0

The security impact metrics below are parsed directly from the CVSS v3.1 vector string (CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:L/I:L/A:H).

Attack Vector Network (AV:N)
Attack Complexity High (AC:H)
Privileges Required None (PR:N)
User Interaction None (UI:N)
Scope Unchanged (S:U)
Confidentiality Low (C:L)
Integrity Low (I:L)
Availability High (A:H)

How to Fix CVE-2026-25087

To remediate this vulnerability, upgrade all affected Apache Arrow dependencies to a patched release. Both direct and transitive dependencies should be checked, as frameworks or security libraries may pull in vulnerable versions transitively.

pyarrow fixed: 23.0.1 
pip install pyarrow>=23.0.1
Verify Direct and Transitive Dependencies

Run the following command in your project directory to verify that all resolved dependencies use the patched release: 

pip show pyarrow

How to Check if You Are Affected

To determine whether your Python environment is affected by CVE-2026-25087, inspect your installed packages using pip:

pip show pyarrow

Analyze the terminal output to locate any version of Apache Arrow in your dependency tree. If any resolved version matches the vulnerable ranges listed in the table below (for example, versions earlier than 23.0.1), your application is affected.

Note: The pip show pyarrow command checks currently installed packages in your active Python environment.

Technical Details

Vulnerability Mechanism & Technical Analysis

This vulnerability is classified under CWE-416: Use After Free, where the product reuses or references memory after it has been freed. at some point afterward, the memory may be allocated again and saved in another pointer, while the original pointer references a location somewhere within the new allocation. any operations using the original pointer are no longer valid because the memory "belongs" to the code that operates on the new pointer. In Apache Arrow, software state validation or input boundaries are circumvented during processing. Review the official source advisory statement below for specific affected components, classes, and reproduction details.

Source Advisory Statement

Use After Free vulnerability in Apache Arrow C++. This issue affects Apache Arrow C++ from 15.0.0 through 23.0.0. It can be triggered when reading an Arrow IPC file (but not an IPC stream) with pre-buffering enabled, if the IPC file contains data with variadic buffers (such as Binary View and String View data). Depending on the number of variadic buffers in a record batch column and on the temporal sequence of multi-threaded IO, a write to a dangling pointer could occur. The value (a `std::shared_ptr<Buffer>` object) that is written to the dangling pointer is not under direct control of the attacker. Pre-buffering is disabled by default but can be enabled using a specific C++ API call (`RecordBatchFileReader::PreBufferMetadata`). The functionality is not exposed in language bindings (Python, Ruby, C GLib), so these bindings are not vulnerable. The most likely consequence of this issue would be random crashes or memory corruption when reading specific kinds of IPC files. If the application allows ingesting IPC files from untrusted sources, this could plausibly be exploited for denial of service. Inducing more targeted kinds of misbehavior (such as confidential data extraction from the running process) depends on memory allocation and multi-threaded IO temporal patterns that are unlikely to be easily controlled by an attacker. Advice for users of Arrow C++: 1. check whether you enable pre-buffering on the IPC file reader (using `RecordBatchFileReader::PreBufferMetadata`) 2. if so, either disable pre-buffering (which may have adverse performance consequences), or switch to Arrow 23.0.1 which is not vulnerable

CVE-2026-25087 Affected Apache Arrow Versions

1 component(s)
Fixed Versions:
23.0.1
Product / Package Ecosystem Affected Versions Fixed Version
pyarrow
pypi/pyarrow
PyPI
≥ 15.0.0
< 23.0.1
23.0.1

References

NVD — CVE-2026-25087 NVD
https://nvd.nist.gov/vuln/detail/CVE-2026-25087
Apache Arrow Source Repository REPOSITORY
https://github.com/apache/arrow/pull/48925
Apache Arrow Source Repository REPOSITORY
https://github.com/apache/arrow
Apache Arrow Source Repository REPOSITORY
https://github.com/pypa/advisory-database/tree/main/vulns/pyarrow/PYSEC-2026-113.yaml
lists.apache.org/thread/mpm4ld1qony3... WEB
https://lists.apache.org/thread/mpm4ld1qony30tchfpjtk5b11tcyvmwh
Apache Arrow Security Information SECURITY
http://www.openwall.com/lists/oss-security/2026/02/17/4

Frequently Asked Questions

What is CVE-2026-25087?
CVE-2026-25087 is a security vulnerability in Apache Arrow involving Potential use-after-free when reading IPC file with pre-buffering under CWE-416: Use After Free.
Which Apache Arrow versions are affected?
Affected versions include releases prior to 23.0.1 across affected packages: pyarrow.
What version fixes CVE-2026-25087?
Upgrading to 23.0.1 (or the latest patched release for your respective branch) resolves the vulnerability.
Is pyarrow affected?
Yes, pyarrow is affected in releases prior to 23.0.1. Upgrade your dependency to 23.0.1 or later.
What is the CVSS score of CVE-2026-25087?
CVE-2026-25087 has a CVSS v3.1 base score of 7.0 (HIGH) with vector string CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:L/I:L/A:H.
What CWE is associated with CVE-2026-25087?
CVE-2026-25087 is classified under CWE-416: Use After Free (The product reuses or references memory after it has been freed. At some point afterward, the memory may be allocated again and saved in another pointer, while the original pointer references a location somewhere within the new allocation. Any operations using the original pointer are no longer valid because the memory "belongs" to the code that operates on the new pointer.).
How can I check PyPI dependencies for CVE-2026-25087?
Run the dependency tree command: 'pip show pyarrow'. This command lists direct and transitive dependencies in your build configuration so you can verify if a vulnerable version is resolved.
Machine-readable OSV JSON OSV v1.5 Schema
Normalized schema output
View Raw JSON 
{
  "schema_version" : "1.4.0",
  "id" : "GHSA-rgxp-2hwp-jwgg",
  "modified" : "2026-06-05T21:39:35Z",
  "published" : "2026-02-17T15:31:35Z",
  "aliases" : [ "CVE-2026-25087" ],
  "summary" : "Apache Arrow: Potential use-after-free when reading IPC file with pre-buffering",
  "details" : "Use After Free vulnerability in Apache Arrow C++.\n\nThis issue affects Apache Arrow C++ from 15.0.0 through 23.0.0. It can be triggered when reading an Arrow IPC file (but not an IPC stream) with pre-buffering enabled, if the IPC file contains data with variadic buffers (such as Binary View and String View data). Depending on the number of variadic buffers in a record batch column and on the temporal sequence of multi-threaded IO, a write to a dangling pointer could occur. The value (a `std::shared_ptr<Buffer>` object) that is written to the dangling pointer is not under direct control of the attacker.\n\nPre-buffering is disabled by default but can be enabled using a specific C++ API call (`RecordBatchFileReader::PreBufferMetadata`). The functionality is not exposed in language bindings (Python, Ruby, C GLib), so these bindings are not vulnerable.\n\nThe most likely consequence of this issue would be random crashes or memory corruption when reading specific kinds of IPC files. If the application allows ingesting IPC files from untrusted sources, this could plausibly be exploited for denial of service. Inducing more targeted kinds of misbehavior (such as confidential data extraction from the running process) depends on memory allocation and multi-threaded IO temporal patterns that are unlikely to be easily controlled by an attacker.\n\nAdvice for users of Arrow C++:\n\n1. check whether you enable pre-buffering on the IPC file reader (using `RecordBatchFileReader::PreBufferMetadata`)\n\n2. if so, either disable pre-buffering (which may have adverse performance consequences), or switch to Arrow 23.0.1 which is not vulnerable",
  "severity" : [ {
    "type" : "CVSS_V3",
    "score" : "CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:L/I:L/A:H"
  } ],
  "affected" : [ {
    "package" : {
      "ecosystem" : "PyPI",
      "name" : "pyarrow"
    },
    "ranges" : [ {
      "type" : "ECOSYSTEM",
      "events" : [ {
        "introduced" : "15.0.0"
      }, {
        "fixed" : "23.0.1"
      } ]
    } ]
  } ],
  "references" : [ {
    "type" : "ADVISORY",
    "url" : "https://nvd.nist.gov/vuln/detail/CVE-2026-25087"
  }, {
    "type" : "WEB",
    "url" : "https://github.com/apache/arrow/pull/48925"
  }, {
    "type" : "PACKAGE",
    "url" : "https://github.com/apache/arrow"
  }, {
    "type" : "WEB",
    "url" : "https://github.com/pypa/advisory-database/tree/main/vulns/pyarrow/PYSEC-2026-113.yaml"
  }, {
    "type" : "WEB",
    "url" : "https://lists.apache.org/thread/mpm4ld1qony30tchfpjtk5b11tcyvmwh"
  }, {
    "type" : "WEB",
    "url" : "http://www.openwall.com/lists/oss-security/2026/02/17/4"
  } ],
  "database_specific" : {
    "cwe_ids" : [ "CWE-416" ],
    "severity" : "HIGH",
    "github_reviewed" : true,
    "github_reviewed_at" : "2026-06-05T21:39:35Z",
    "nvd_published_at" : "2026-02-17T14:16:01Z"
  }
}